This site uses cookies to improve your experience. To help us insure we adhere to various privacy regulations, please select your country/region of residence. If you do not select a country, we will assume you are from the United States. Select your Cookie Settings or view our Privacy Policy and Terms of Use.
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Used for the proper function of the website
Used for monitoring website traffic and interactions
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Strictly Necessary: Used for the proper function of the website
Performance/Analytics: Used for monitoring website traffic and interactions
On a different project, we’d just used a LargeLanguageModel (LLM) - in this case OpenAI’s GPT - to provide users with pre-filled text boxes, with content based on choices they’d previously made. This gives Mark more control over the process, without requiring him to write much, and gives the LLM more to work with.
What if the principles that transformed softwaredevelopment over the last decade could be the key to successfully implementing AI in your organization? Patrick Debois is credited with coining the term “DevOps” and has been instrumental in shaping how organizations approach softwaredevelopment and operations.
But while the increasing number of companies adopting VSM has changed how teams build from project to product, a new innovative approach hits the spotlight: generativeAI (genAI). In essence, AImodels can take inputs in various forms and generate new content based on the modality of the model.
The softwaredevelopment methodologies and organizational design principles harnessed by digital natives are well documented. The latest advances in generativeAI and LargeLanguageModels (LLMs) have become ubiquitously available at an unprecedented rate.
The idea of cutting waste, a principle from manufacturing, is relevant more than ever in softwaredevelopment and knowledge work as a means to increase efficiency. This highlights the critical need for understanding where waste is coming from within the software delivery lifecycle and developing strategies to mitigate it.
Standing on the precipice of today’s artificialintelligence revolution, we find an uncanny parallel to the Luddite’s chapter in history. As Chief Data Scientist at Planview, I believe we can be pro-technology while remaining staunchly pro-human, implementing AI on behalf of our customers as a force for good.
Recent advancements in GenerativeAI and machinelearning (ML) have enthralled enterprises and consumers alike, as we recently saw with the launch of GPT-4. The Power Platform package also includes Power Apps, which uses AI to generate low-code applications with extensive customization options.
As we step into 2025, a new paradigm is emerging in softwaredevelopment: the era of the LLM-native developer. This transformation isnt about replacing developers with AI but redefining their roles. Take biotech drug development, for example. However, these boundaries are fading.
We organize all of the trending information in your field so you don't have to. Join 29,000+ users and stay up to date on the latest articles your peers are reading.
You know about us, now we want to get to know you!
Let's personalize your content
Let's get even more personalized
We recognize your account from another site in our network, please click 'Send Email' below to continue with verifying your account and setting a password.
Let's personalize your content